[英]Adding two smaller subplots to the side of my main plot in matplotlib subplots
目前我的圖表僅顯示左側的主要大圖表。
但是,我現在想將兩個較小的圖添加到主 plot 的右側; 與每個單獨的數據集。
我正在努力研究如何做到這一點。 下面的照片顯示了我想要的 output。
filenamesK = glob("C:/Users/Ke*.csv")
filenamesZ = glob("C:/Users/Ze*.csv")
K_Z_Averages = {'K':[], 'Z':[]}
# We will create a function for plotting, instead of nesting lots of if statements within a long for-loop.
def plot_data(filename, fig_ax, color):
df = pd.read_csv(f, sep=',',skiprows=24) # Read in the csv.
df.columns=['sample','Time','ms','Temp1'] # Set the column names
df=df.astype(str) # Set the data type as a string.
df["Temp1"] = df["Temp1"].str.replace('\+ ', '').str.replace(' ', '').astype(float) # Convert to float
# Take the average of the data from the Temp1 column, starting from sample 60 until sample 150.
avg_Temp1 = df.iloc[60-1:150+1]["Temp1"].mean()
# Append this average to a K_Z_Averages, containing a column for average from each K file and the average from each Z file.
# Glob returns the whole path, so you need to replace 0 for 10.
K_Z_Averages[os.path.basename(filename)[0]].append(avg_Temp1)
fig_ax.plot(df[["Temp1"]], color=color)
fig, ax = plt.subplots(figsize=(20, 15))
for f in filenamesK:
plot_data(f, ax, 'blue')
for f in filenamesZ:
plot_data(f, ax, 'red')
plt.show()
@max 的答案很好,但你也可以做 matplotlib>=3.3 是
import matplotlib.pyplot as plt
fig = plt.figure(constrained_layout=True)
axs = fig.subplot_mosaic([['Left', 'TopRight'],['Left', 'BottomRight']],
gridspec_kw={'width_ratios':[2, 1]})
axs['Left'].set_title('Plot on Left')
axs['TopRight'].set_title('Plot Top Right')
axs['BottomRight'].set_title('Plot Bottom Right')
請注意,重復的名稱'Left'
被使用了兩次,表示該子圖在布局中占據了兩個位置。 還要注意width_ratios
的使用。
這是一個棘手的問題。 本質上,您可以在圖形上放置一個網格 ( add_gridspec()
add_subplot()
),然后在不同的網格元素中打開子圖 ( add_subplot() )。
import matplotlib.pyplot as plt
# open figure
fig = plt.figure()
# add grid specifications
gs = fig.add_gridspec(2, 3)
# open axes/subplots
axs = []
axs.append( fig.add_subplot(gs[:,0:2]) ) # large subplot (2 rows, 2 columns)
axs.append( fig.add_subplot(gs[0,2]) ) # small subplot (1st row, 3rd column)
axs.append( fig.add_subplot(gs[1,2]) ) # small subplot (2nd row, 3rd column)
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